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» Improving heuristic mini-max search by supervised learning
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FLAIRS
2007
13 years 9 months ago
Search Ordering Heuristics for Restarts-Based Constraint Solving
Constraint Satisfaction Problems are ubiquitous in Artificial Intelligence. Over the past decade significant advances have been made in terms of the size of problem instance tha...
Margarita Razgon, Barry O'Sullivan, Gregory M. Pro...
COR
2010
146views more  COR 2010»
13 years 7 months ago
A search space "cartography" for guiding graph coloring heuristics
We present a search space analysis and its application in improving local search algorithms for the graph coloring problem. Using a classical distance measure between colorings, w...
Daniel Cosmin Porumbel, Jin-Kao Hao, Pascale Kuntz
MLDM
2005
Springer
14 years 29 days ago
Using Clustering to Learn Distance Functions for Supervised Similarity Assessment
Assessing the similarity between objects is a prerequisite for many data mining techniques. This paper introduces a novel approach to learn distance functions that maximizes the c...
Christoph F. Eick, Alain Rouhana, Abraham Bagherje...
CPAIOR
2008
Springer
13 years 9 months ago
The Accuracy of Search Heuristics: An Empirical Study on Knapsack Problems
Theoretical models for the evaluation of quickly improving search strategies, like limited discrepancy search, are based on specific assumptions regarding the probability that a va...
Daniel H. Leventhal, Meinolf Sellmann
ICDM
2006
IEEE
131views Data Mining» more  ICDM 2006»
14 years 1 months ago
Dimension Reduction for Supervised Ordering
Ordered lists of objects are widely used as representational forms. Such ordered objects include Web search results and best-seller lists. Techniques for processing such ordinal d...
Toshihiro Kamishima, Shotaro Akaho